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Boolean analysis was introduced by Flament (1976). The goal of a Boolean analysis is to detect deterministic dependencies between the items of a questionnaire or similar data-structures in observed response patterns. These deterministic dependencies have the form of logical formulas connecting the items. Assume, for example, that a questionnaire contains items ''i'', ''j'', and ''k''. Examples of such deterministic dependencies are then ''i'' → ''j'', ''i'' ∧ ''j'' → ''k'', and ''i'' ∨ ''j'' → ''k''. Since the basic work of Flament (1976) a number of different methods for Boolean analysis have been developed. See, for example, Buggenhaut and Degreef (1987), Duquenne (1987), item tree analysis Leeuwe (1974), Schrepp (1999), or Theuns (1998). These methods share the goal to derive deterministic dependencies between the items of a questionnaire from data, but differ in the algorithms to reach this goal. Boolean analysis is an explorative method to detect deterministic dependencies between items. The detected dependencies must be confirmed in subsequent research. Methods of Boolean analysis do not assume that the detected dependencies describe the data completely. There may be other probabilistic dependencies as well. Thus, a Boolean analysis tries to detect interesting deterministic structures in the data, but has not the goal to uncover all structural aspects in the data set. Therefore, it makes sense to use other methods, like for example latent class analysis, together with a Boolean analysis. == Application areas == The investigation of deterministic dependencies has some tradition in educational psychology. The items represent in this area usually skills or cognitive abilities of subjects. Bart and Airasian (1974) use Boolean analysis to establish logical implications on a set of Piagetian tasks. Other examples in this tradition are the learning hierarchies of Gagné (1968) or the theory of structural learning of Scandura (1971). There are several attempts to use boolean analysis, especially item tree analysis to construct knowledge spaces from data. Examples can be found in Held and Korossy (1998), or Schrepp (2002). Methods of Boolean analysis are used in a number of social science studies to get insight into the structure of dichotomous data. Bart and Krus (1973) use, for example, Boolean analysis to establish a hierarchical order on items that describe socially unaccepted behavior. Janssens (1999) used a method of Boolean analysis to investigate the integration process of minorities into the value system of the dominant culture. Romme (1995a) introduced Boolean comparative analysis to the management sciences, and applied it in a study of self-organizing processes in management teams (Romme 1995b). 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Boolean analysis」の詳細全文を読む スポンサード リンク
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